The present invention relates to a method for encoding audio signals using human auditory characteristics, and more particularly, to an encoding method for improving the speed of bit allocating operation.
Along with the recent development of digital signal processing technology, existing audio instrumentation is undergoing rapid replacement. That is, laser disk players (LDPs) or tape recorders for recording/reproducing analog audio signals are being supplanted with the systems adopting compact disks (CDs), digital audio tapes (DATs) or MiniDiscs (MDs) for recording/reproducing digital audio signals. Here, the digital processing of an audio signal improves sound quality, but results in the adverse effect of greatly increasing data quantity.
The above data-quantity problem can be alleviated by selectively removing signal components which are undetectable by the human ear and adaptively allocating a number of quantization bits to those components which can be perceived. This is accomplished by digital compact cassettes, MiniDiscs, or an MPEG (Moving Pictures Expert Group) audio system whose standardization has been recently set by the International Organization for Standardization. The main objective of such an encoding method is not removing generated noise but processing the noise not so as to be perceived, by adaptively allocating the number of quantization bits according to signal weight in consideration of a masking effect and critical bands. Here, the masking effect is a phenomenon wherein the sound (audio component) which should be heard is disturbed or masked completely by other sounds, and the critical bands are frequency bands in which signal and noise components cannot be differentiated from each other in frequency domain when their frequency and power characteristics are respectively similar to each other.
In the method of encoding using characteristics of the human auditory system, the encoding is performed in consideration of the aforementioned masking phenomenon. A masking threshold is first obtained. The masking threshold changes due to an interaction between input signals and is the minimum magnitude of a signal which is heard but cannot be discerned. The undiscernible signal is not allocated with quantization bits, but the signal component which is important for the comprehension of the sound is adaptively allocated with a number quantization bits, thereby obtaining a data compression effect.
Various measures have been proposed for locating the signal which plays the determining role in sound perception, using an input signal and the masking threshold of the input signal. The typically employed technique is to obtain a noise-to-mask ratio (NMR) which is the ratio of an error noise component (noise due to an error value based on quantization in each band) to the masking threshold. This noise-to-mask ratio indicates the gap between the masking threshold and the error component.
As can be shown by acoustic experimentation, if noise is present at levels near the masking threshold, the noise is difficult to detect, and if below the masking threshold, detection is impossible. Thus, it is important to know the gap between the error signal and the masking threshold.
The NMR concept was originally adopted in 1987 as one factor for considering the aforementioned characteristic regarding the masking threshold, and indicates the audible extent of the error signal in view of human psychoacoustic properties.
The noise-to-mask ratio is determined by obtaining the signal-to-mask ratio (SMR) and performing a relational operation of the obtained SMR value and an SNR value which is the ratio of a quantized error signal to the error noise.
The method of allocating the number of quantization bits with respect to perceivable sound components is described below, in terms of a conventional encoding method.
1. The number of bits allocated to all critical bands is initialized (set to zero) and NMR values are computed for all critical bands.
2. The critical band having the largest NMR value is searched, and one bit is allocated to the searched critical band.
3. The NMR values for all critical bands are computed newly, and step 2 is repeated until all the available quantization bits are depleted.
According to the aforementioned conventional bit allocation method, after performing relational operations a certain number of times (the number of processed bands minus one) when one bit is allocated, an addition operation is further required. For example, if the number of critical bands is twenty four, in order for N quantization bits to be allocated for a given band, N(24-1) relational operations and N addition operations are required. Therefore, with such an iterative bit-allocation method, manifold operations are needed, which thus complicates the hardware configuration.